Image Classification
Transformers
PyTorch
TensorBoard
Safetensors
swin
Generated from Trainer
Eval Results (legacy)
Instructions to use gianlab/swin-tiny-patch4-window7-224-finetuned-ecg-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gianlab/swin-tiny-patch4-window7-224-finetuned-ecg-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="gianlab/swin-tiny-patch4-window7-224-finetuned-ecg-classification") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("gianlab/swin-tiny-patch4-window7-224-finetuned-ecg-classification") model = AutoModelForImageClassification.from_pretrained("gianlab/swin-tiny-patch4-window7-224-finetuned-ecg-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from gianlab/swin-tiny-patch4-window7-224-finetuned-ecg-classification: direct link, hf CLI and curl.
- Browser
- Download file 110 MB
-
https://huggingface.co/gianlab/swin-tiny-patch4-window7-224-finetuned-ecg-classification/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://gianlab/swin-tiny-patch4-window7-224-finetuned-ecg-classification/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/gianlab/swin-tiny-patch4-window7-224-finetuned-ecg-classification/resolve/main/pytorch_model.bin
110 MB
- Xet hash:
- 1d92965c1d8102602adf435bfcff46aab290a53517cdea82f87a0c4d012cd4c4
- Size of remote file:
- 110 MB
- SHA256:
- 9d449c3b468f1ceca40960151735b8a472d938437ba6947dc277b0289eb8e628
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.